A Review of Gearbox Condition Monitoring Based on vibration Analysis Techniques Diagnostics and Prognostics

Sait, Abdulrahman S.; Sharaf-Eldeen, Yahya I.

doi:10.1007/978-1-4419-9428-8_25

Cited by 78 publications

(43 citation statements)

References 13 publications

(19 reference statements)

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…In application to diagnosis of machine faults, simple AE parameters are typically employed, such as rms, kurtosis, AE counts [41] and demodulation [38]. More [58], Wigner-Ville [56], and wavelet analysis [59; 60]. The use of these detection techniques are feasible for applications where a single component is being monitored however for applications that include several components, such as gearboxes, it is essential to employ separation algorithms.…”

Section: Gear and Bearing Diagnosismentioning

confidence: 99%

A comparative study of the effectiveness of vibration and acoustic emission in diagnosing a defective bearing in a planetry gearbox

et al. 2017

View full text Add to dashboard Cite

Whilst vibration analysis of planetary gearbox faults is relatively well established, the application of Acoustic Emission (AE) to this field is still in its infancy. For planetary-type gearboxes it is more challenging to diagnose bearing faults due to the dynamically changing transmission paths which contribute to masking the vibration signature of interest.The present study is aimed to reduce the effect of background noise whilst extracting the fault feature from AE and vibration signatures. This has been achived through developing of internal AE sensor for helicopter transmission system. In addition, series of signal processing procedure has been developed to improved detection of incipient damage. Three signal processing techniques including an adaptive filter, spectral kurtosis and envelope analysis, were applied to AE and vibration data acquired from a simplified planetary gearbox test rig with a seeded bearing defect. The results show that AE identified the defect earlier than vibration analysis irrespective of the tortuous transmission path.

show abstract

Section: Gear and Bearing Diagnosismentioning

confidence: 99%

A comparative study of the effectiveness of vibration and acoustic emission in diagnosing a defective bearing in a planetry gearbox

et al. 2017

View full text Add to dashboard Cite

show abstract

“…5 Reviews covering the state of the art of health condition monitoring for rotating machinery have already been published focusing on the methodologies and algorithms of PHM in rotating equipment, 9,21 and specific techniques such as the empirical mode decomposition for fault diagnosis 22 and vibration analysis. 23 However, the state of the art of PbM for rotating machinery has not been reviewed in depth; papers focused on PHM for rotating machinery normally include a section mentioning significant PbM approaches, but the description of the principles behind those models is limited. This article describes the principles behind the most relevant PbM for rotating machinery and the factors that have to be taken into account when selecting a model for PHM are discussed.…”

Section: Introductionmentioning

confidence: 99%

A review of physics-based models in prognostics: Application to gears and bearings of rotating machinery

Cubillo

Perinpanayagam

Esperon-Miguez

2016

Advances in Mechanical Engineering

182

View full text Add to dashboard Cite

Health condition monitoring for rotating machinery has been developed for many years due to its potential to reduce the cost of the maintenance operations and increase availability. Covering aspects include sensors, signal processing, health assessment and decision-making. This article focuses on prognostics based on physics-based models. While the majority of the research in health condition monitoring focuses on data-driven techniques, physics-based techniques are particularly important if accuracy is a critical factor and testing is restricted. Moreover, the benefits of both approaches can be combined when data-driven and physics-based techniques are integrated. This article reviews the concept of physics-based models for prognostics. An overview of common failure modes of rotating machinery is provided along with the most relevant degradation mechanisms. The models available to represent these degradation mechanisms and their application for prognostics are discussed. Models that have not been applied to health condition monitoring, for example, wear due to metal-metal contact in hydrodynamic bearings, are also included due to its potential for health condition monitoring. The main contribution of this article is the identification of potential physics-based models for prognostics in rotating machinery.

show abstract

“…Diagnostic parameters used in time domain are presented in Fig. 1, more information about these parameters can be found in [6,10,14,16,19,21,24,25,26,38,39]. Some of them can be also used in frequency and in time-frequency domains.…”

Section: Science and Technologymentioning

confidence: 99%

Evaluation of the spur gear condition using extended frequency range

Skrickij¹,

Bogdevičius²,

Žygienė³

2017

EiN

View full text Add to dashboard Cite

show abstract

A Review of Gearbox Condition Monitoring Based on vibration Analysis Techniques Diagnostics and Prognostics

Cited by 78 publications

References 13 publications

A comparative study of the effectiveness of vibration and acoustic emission in diagnosing a defective bearing in a planetry gearbox

A comparative study of the effectiveness of vibration and acoustic emission in diagnosing a defective bearing in a planetry gearbox

A review of physics-based models in prognostics: Application to gears and bearings of rotating machinery

Evaluation of the spur gear condition using extended frequency range

Contact Info

Product

Resources

About